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Regional climate modelling over complex terrain: an evaluation study of COSMO-CLM hindcast model runs for the Greater Alpine Region

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Abstract

In this study the results of the regional climate model COSMO-CLM (CCLM) covering the Greater Alpine Region (GAR, 4°–19°W and 43°–49°N) were evaluated against observational data. The simulation was carried out as a hindcast run driven by ERA-40 reanalysis data for the period 1961–2000. The spatial resolution of the model data presented is approx. 10 km per grid point. For the evaluation purposes a variety of observational datasets were used: CRU TS 2.1, E-OBS, GPCC4 and HISTALP. Simple statistics such as mean biases, correlations, trends and annual cycles of temperature and precipitation for different sub-regions were applied to verify the model performance. Furthermore, the altitude dependence of these statistical measures has been taken into account. Compared to the CRU and E-OBS datasets CCLM shows an annual mean cold bias of −0.6 and −0.7 °C, respectively. Seasonal precipitation sums are generally overestimated by +8 to +23 % depending on the observational dataset with large variations in space and season. Bias and correlation show a dependency on altitude especially in the winter and summer seasons. Temperature trends in CCLM contradict the signals from observations, showing negative trends in summer and autumn which are in contrast to CRU and E-OBS.

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References

  • Auer I, Böhm R, Jurkovic A, Lipa W, Orlik A, Potzmann R, Schöner W, Ungersböck M, Matulla C, Briffa K, Jones P, Efthymiadis D, Brunetti M, Nanni T, Maugeri M, Mercalli L, Mestre O, Moisselin J-M, Begert M, Müller-Westermeier G, Kveton V, Bochnicek O, Stastny P, Lapin M, Szalai S, Szentimrey T, Cegnar T, Dolinar M, Gajic-Capka M, Zaninovic K, Majstorovic Z, Nieplova E (2007) HISTALP—historical instrumental climatological surface time series of the Greater Alpine Region. Int J Clim 27:17–46

    Article  Google Scholar 

  • Bachner S, Kapala A, Simmer C (2008) Evaluation of daily precipitation characteristics in the CLM and their sensitivity to parameterizations. Meteorol Z 17:407–419. doi:10.1127/0941-2948/2008/0300

    Article  Google Scholar 

  • Boberg F, Berg P, Thejll P, Gutowski WJ, Christensen JH (2009) Improed confidence in climate change projections of precipitation evaluated using daily statistics from the PRUDENCE ensemble. Clim Dyn 32:1097–1106. doi:10.1007/s00382-008-0446-y

    Article  Google Scholar 

  • Boberg F, Berg P, Thejll P, Gutowski WJ, Christensen JH (2010) Improved confidence in climate change projections of precipitation further evaluated using daily statistics from ENSEMBLES models. Clim Dyn 35:1509–1520. doi:10.1007/s00382-009-0683-8

    Article  Google Scholar 

  • Böhm U, Kücken M, Ahrens W, Block A, Hauffe D, Keuler K, Rockel B, Will A (2006) CLM—the climate version of LM: brief description and long-term applications. COSMO Newslett 6:225–235

    Google Scholar 

  • Brinkmann WAR (1971) What is foehn? Weather 26:230–239

    Article  Google Scholar 

  • Bucchignani E, Sanna A, Gualdi S, Castellari S, Schiano P (2011) Simulation of the climate of the XX century in the Alpine space. Nat Hazards. doi:10.1007/s11069-011-9883-8

    Google Scholar 

  • Ceppi P, Scherrer SC, Fischer AM, Appenzeller C (2010) Revisiting Swiss temperature trends 1959–2008. Int J Clim. doi:10.1002/joc.2260

    Google Scholar 

  • Chimani B, Böhm R, Matulla C, Ganekind M (2011) Development of a longterm dataset of solid/liquid precipitation. Adv Sci Res 6:39–43

    Article  Google Scholar 

  • Christensen JH, Carter TR, Giorgi F (2002) PRUDENCE employs new methods to assess European climate change. Eos 83:147

    Article  Google Scholar 

  • Christensen JH, Carter TR, Rummukainen M, Amanatidis G (2007) Evaluating the performance and utility of regional climate models: the PRUDENCE project. Clim Change 81:1–6. doi:10.1007/s10584-006-9211-6

    Article  Google Scholar 

  • Daly C (2006) Guidelines for assessing the suitability of spatial climate data sets. Int J Clim 26:707–721

    Article  Google Scholar 

  • Davin EL, Stöckli R, Jaeger EB, Levis S, Seneviratne SI (2011) COSMO-CLM2: a new version of the COSMO-CLM model coupled to the community land model. Clim Dyn. doi:10.1007/s00382-011-1019-z

    Google Scholar 

  • Dickinson R, Henderson-Sellers A, Kennedy P, Wilson M (1986) Biosphere-atmosphere transfer scheme (bats) forcing ncar community climate model. NCAR Technical Note TN275+STR, NCAR

  • Dobler A, Ahrens B (2008) Precipitation by a regional climate model and bias correction in Europe and South Asia. Meteorol Z 17:499–510

    Article  Google Scholar 

  • Doms G, Förster J, Heise E, Herzog HJ, Raschendorfer M, Schrodin R, Reinhardt T, Vogel G (2002) A description of the nonhydrostatic regional model LM. Part II: physical parametrization. Technical report, Deutscher Wetterdienst, Offenbach

  • Douglass D, Pearson D, Singer F (2004) Altitude dependence of atmospheric temperature trends: climate models versus observation. Geophys Res Lett 31. doi:10.1029/2004GL020103

  • Efthymiadis D, Jones PD, Briffa KR, Auer I, Böhm R, Schöner W, Frei C, Schmidli J (2006) Construction of a 10-min-gridded precipitation data set for the Greater Alpine Region for 1800–2003. J Geophys Res 111:D01105

    Article  Google Scholar 

  • Ensor LA, Robeson SM (2008) Statistical characteristics of daily precipitation: comparisons of gridded and point datasets. J Appl Meteor 47:2468–2476. doi:10.1175/2008JAMC1757.1

    Article  Google Scholar 

  • Feldmann H, Früh B, Schädler G, Panitz H-J, Keuler K, Jacob D, Lorenz P (2008) Evaluation of the precipitation for South-western Germany from high resolution simulations with regional climate models. Meteorol Z 17:455–466

    Article  Google Scholar 

  • Frei C, Christensen JH, Déqué M, Jacob D, Jones R, Vidale PL (2003) Daily precipitation statistics in regional climate models: evaluation and intercomparison for the European Alps. J Geophys Res 108. doi:10.1029/2002JD002287

  • Haylock MR, Cawley GC, Harpham C, Wilby RL, Goodess C (2006) Downscaling heavy precipitation over the UK: a comparison of dynamical and statistical methods and their future scenarios. Int J Clim 26:1397–1415. doi:10.1002/joc.1318

    Article  Google Scholar 

  • Haylock MR, Hofstra N, Klein Tank AMG, Klok EJ, Jones PD, New M (2008) A European daily high-resolution gridded data set of surface temperature and precipitation for 1950–2006. J Geophys Res 113. doi:10.1029/2008JD010201

  • Hewitt C (2005) The ENSEMBLES project. EGU Newslett 13:22–25

    Google Scholar 

  • Hofstra N, Haylock M, New M, Jones P, Frei C (2008) Comparison of six methods for the interpolation of daily, European climate data. J Geophys Res 113:D21110. doi:10.1029/2008JD010100

  • Hofstra N, New M, McSweeney C (2009a) The influence of interpolation and station network density on the distributions and trends of climate variables in gridded daily data. Clim Dyn. doi:10.1007/s00382-009-0698-1

    Google Scholar 

  • Hofstra N, Haylock M, New M and Jones P (2009b) Testing E-OBS European high-resolution gridded data set of daily precipitation and surface temperature. J Geophys Res 114:D21101. doi:10.1029/2009JD011799

  • Hollweg H-D, Böhm U, Fast I, Hennemuth B, Keuler K, Keup-Thiel E, Lautenschlager M, Legutke S, Radtke K, Rockel B, Schubert M, Will A, Woldt M, Wunram C (2008) Ensemble simulations over Europe with the regional climate model CLM forced with IPCC AR4 global scenarios. Technical Report 3, Max-Planck-Institut für Meteorologie, Hamburg

  • Jacob D, Bärring L, Christensen OB, Christensen JH, Castro M, Déqué M, Giorgi F, Hagemann S, Hirschi M, Jones R, Kjellström E, Lenderink G, Rockel B, Sánchez E, Schär C, Seneviratne SI, Somot S, Ulden A, Hurk B (2007) An inter-comparison of regional climate models for Europe: model performance in present-day climate. Clim Change 81:31–52. doi:10.1007/s10584-006-9213-4

    Article  Google Scholar 

  • Jaeger EB, Seneviratne SI (2010) Impact of soil moisture–atmosphere coupling on European climate extremes and trends in a regional climate model. Clim Dyn 36:1919–1939. doi:10.1007/s00382-010-0780-8

    Article  Google Scholar 

  • Jaeger EB, Anders I, Lüthi D, Rockel B, Schär C, Seneviratne SI (2008) Analysis of ERA40 driven CLM simulations for Europe. Meteorol Z 17:349–367

    Article  Google Scholar 

  • Kain JS, Fritsch JM (1993) A one-dimensional entraining de-training plume model and its application in convective parameterization. J Atmos Sci 23:2784–2802

    Google Scholar 

  • Kjellström E, Boberg F, Castro M, Christensen J, Nikulin G, Sánchez E (2010) Daily and monthly temperature and precipitation statistics as performance indicators for regional climate models. Clim Res 44:135–150. doi:10.3354/cr00932

    Article  Google Scholar 

  • Kotlarski S, Block A, Böhm U, Jacob D, Keuler K, Knoche R, Rechid D, Walter A (2005) Regional climate model simulations as input for hydrological applications: evaluation of uncertainties. Adv Geosci 5:119–125

    Article  Google Scholar 

  • Kotlarski S, Paul F, Jacob D (2010) Forcing a distributed glacier mass balance model with the regional climate model REMO. Part I: climate model evaluation. J Clim 23:1589–1606. doi:10.1175/2009JCLI2711.1

    Article  Google Scholar 

  • Mitchell TD, Jones PD (2005) An improved method of constructing a database of monthly climate observations and associated high-resolution grids. Int J Clim 25:693–712. doi:10.1002/joc.1181

    Article  Google Scholar 

  • Nikulin G, KjellströM E, Hansson U, Strandberg G, Ullerstig A (2011) Evaluation and future projections of temperature, precipitation and wind extremes over Europe in an ensemble of regional climate simulations. Tellus A 63:41–55. doi:10.1111/j.1600-0870.2010.00466.x

    Article  Google Scholar 

  • Perry MC, Hollis DM (2005) The generation of monthly gridded datasets for a range of climatic variables over the UK. Int J Clim 25:1041–1054

    Article  Google Scholar 

  • Rockel B, Geyer B (2008) The performance of the regional climate model CLM in different climate regions, based on the example of precipitation. Meteorol Z 17:487–498. doi:10.1127/0941-2948/2008/0297

    Article  Google Scholar 

  • Roe GH (2005) Orographic precipitation. Annu Rev Earth Planet Sci 33:645–671. doi:10.1146/annurev.earth.33.092203.122541

    Article  Google Scholar 

  • Roesch A, Jaeger EB, Lüthi D, Seneviratne SI (2008) Analysis of CCLM model biases in relation to intra ensemble model variability. Meteorol Z 17:369–382

    Article  Google Scholar 

  • Rudolf B, Becker A, Schneider U, Meyer-Christoffer A, Ziese M (2011) New GPCC full data reanalysis version 5 provides high-quality gridded monthly precipitation data. GEWEX News 21(2):4–5

    Google Scholar 

  • Schmidli J, Frei C, Schär C (2001) Reconstruction of mesoscale precipitation fields from sparse observations in complex terrain. J Clim 14:3289–3306

    Article  Google Scholar 

  • Schmidli J, Goodess C, Frei C, Haylock M, Hundecha Y, Ribalaygua J, Schmith T (2007) Statistical and dynamical downscaling of precipitation: an evaluation and comparison of scenarios for the European Alps. J Geophys Res 112

  • Schneider U, Fuchs T, Meyer-Christoffer A, Rudolf B (2008) Global precipitation analysis products of the GPCC. Deutscher Wetterdienst, Offenbach

    Google Scholar 

  • Schrodin R, Heise E (2001) The multi-layer version of the DWD soil model TERRA-LM. COSMO technical report 2, Deutscher Wetterdienst

  • Seibert P (1990) South foehn studies since the ALPEX experiment. Meteorol Atmos Phys 43:91–103

    Article  Google Scholar 

  • Smiatek G, Kunstmann H, Knoche R, Marx A (2009) Precipitation and temperature statistics in high-resolution regional climate models: evaluation for the European Alps. J Geophys Res 114

  • Stahl K, Moore RD, Floyer JA, Asplin MG, McKendry IG (2006) Comparison of approaches for spatial interpolation of daily air temperature in a large region with complex topography and highly variable station density. Agric Forest Meteorol 139:224–236

    Article  Google Scholar 

  • Suklitsch M, Gobiet A, Leuprecht A, Frei C (2008) High resolution sensitivity studies with the regional climate model cclm in the Alpine region. Meteorol Z 17:467–476. doi:10.1127/0941-2948/2008/0308

    Article  Google Scholar 

  • Suklitsch M, Gobiet A, Truhetz H, Awan NK, Göttel H, Jacob D (2010) Error characteristics of high resolution regional climate models over the Alpine area. Clim Dyn 37:377–390. doi:10.1007/s00382-010-0848-5

    Article  Google Scholar 

  • Uppala SM, Kaallberg P, Simmons A, Andrae U, Bechtold V, Fiorino M, Gibson J, Haseler J, Hernandez A, Kelly G et al (2005) The ERA-40 re-analysis. Q J Roy Meteorol Soc 131:2961–3012

    Article  Google Scholar 

  • van der Linden P, Mitchell JFB (2009) ENSEMBLES: climate change and its impacts: summary of research and results from the ENSEMBLES project. Met Office Hadley Centre, FitzRoy Road, Exeter EX1 3 PB, UK

  • van Engelen A, Klein Tank AMG, van de Schrier G, Klok L (2008) Towards an operational system for assessingobserved changes in climate extremes. European Climate Assessment & Dataset (ECA&D) Report

  • Whiteman CD (1990) Observations of thermally developed wind systems in mountainous terrain. In: Blumen W (ed) Chapter 2 in atmospheric processes over complex terrain. Meteorological Monographs, American Meteorological Society, Boston, pp 5–42

    Google Scholar 

  • Wilks DS (2006) Statistical methods in the atmospheric sciences, volume 91, second edition (international geophysics). Academic Press, Burlington

    Google Scholar 

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Acknowledgments

The regional climate simulations described in this study were conducted within the framework of the RECLIP:CENTURY project, funded by the Austrian Climate Research Programme. The analysis of the simulation results was carried out in the course of the EVACLIM project, founded by the Austrian Federal Ministry of Science and Research. The authors would like to thank the COSMO-CLM community for providing access to and support for the model, as well as Klaus Keuler for his comments on our simulation results. The R DEVELOPMENT CORE TEAM is acknowledged for providing the statistics package “R”. Finally, the authors would like to thank two anonymous reviewers for their valuable comments which improved the manuscript substantially.

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  1. Climate Research Department, Zentralanstalt für Meteorologie und Geodynamik (ZAMG), Hohe Warte 38, 1190, Vienna, Austria

    Klaus Haslinger, Ivonne Anders & Michael Hofstätter

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  1. Klaus Haslinger
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Correspondence to Klaus Haslinger.

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Haslinger, K., Anders, I. & Hofstätter, M. Regional climate modelling over complex terrain: an evaluation study of COSMO-CLM hindcast model runs for the Greater Alpine Region. Clim Dyn 40, 511–529 (2013). https://doi.org/10.1007/s00382-012-1452-7

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